Antisense-Mediated RNA Targeting: Versatile and Expedient Genetic Manipulation in the Brain

A limiting factor in brain research still is the difficulty to evaluate in vivo the role of the increasing number of proteins implicated in neuronal processes. We discuss here the potential of antisense-mediated RNA targeting approaches. We mainly focus on those that manipulate splicing (exon skipping and exon inclusion), but will also briefly discuss mRNA targeting. Classic knockdown of expression by mRNA targeting is only one possible application of antisense oligonucleotides (AON) in the control of gene function. Exon skipping and inclusion are based on the interference of AONs with splicing of pre-mRNAs. These are powerful, specific and particularly versatile techniques, which can be used to circumvent pathogenic mutations, shift splice variant expression, knock down proteins, or to create molecular models using in-frame deletions. Pre-mRNA targeting is currently used both as a research tool, e.g., in models for motor neuron disease, and in clinical trials for Duchenne muscular dystrophy and amyotrophic lateral sclerosis. AONs are particularly promising in relation to brain research, as the modified AONs are taken up extremely fast in neurons and glial cells with a long residence, and without the need for viral vectors or other delivery tools, once inside the blood brain barrier. In this review we cover (1). The principles of antisense-mediated techniques, chemistry, and efficacy. (2) The pros and cons of AON approaches in the brain compared to other techniques of interfering with gene function, such as transgenesis and short hairpin RNAs, in terms of specificity of the manipulation, spatial, and temporal control over gene expression, toxicity, and delivery issues. (3) The potential applications for Neuroscience. We conclude that there is good evidence from animal studies that the central nervous system can be successfully targeted, but the potential of the diverse AON-based approaches appears to be under-recognized

Iron accumulation induces oxidative stress, while depressing inflammatory polarization in human iPSC-derived microglia

Iron accumulation in microglia has been observed in Alzheimer’s disease and other neurodegenerative disorders and is thought to contribute to disease progression through various mechanisms, including neuroinflammation. To study this interaction, we treated human induced pluripotent stem cell-derived microglia (iPSC-MG) with iron, in combination with inflammatory stimuli such as interferon gamma (IFN-γ) and amyloid β. Both IFN-γ and iron treatment increased labile iron levels, but only iron treatment led to a consistent increase of ferritin levels, reflecting long-term iron storage. Therefore, in iPSC-MG, ferritin appeared to be regulated by iron revels rather than inflammation. Further investigation showed that while IFN-γ induced pro-inflammatory activation, iron treatment dampened both classic pro- and anti-inflammatory activation on a transcriptomic level. Notably, iron-loaded microglia showed strong upregulation of cellular stress response pathways, the NRF2 pathway, and other oxidative stress pathways. Functionally, iPSC-MG exhibited altered phagocytosis and impaired mitochondrial metabolism following iron treatment. Collectively, these data suggest that in MG, in contrast to current hypotheses, iron treatment does not result in pro-inflammatory activation, but rather dampens it and induces oxidative stress

Mutant huntingtin activates Nrf2-responsive genes and impairs dopamine synthesis in a PC12 model of Huntington's disease

<p>Abstract</p> <p>Background</p> <p>Huntington's disease is a progressive autosomal dominant neurodegenerative disorder that is caused by a CAG repeat expansion in the HD or Huntington's disease gene. Although micro array studies on patient and animal tissue provide valuable information, the primary effect of mutant huntingtin will inevitably be masked by secondary processes in advanced stages of the disease. Thus, cell models are instrumental to study early, direct effects of mutant huntingtin. mRNA changes were studied in an inducible PC12 model of Huntington's disease, before and after aggregates became visible, to identify groups of genes that could play a role in the early pathology of Huntington's disease.</p> <p>Results</p> <p>Before aggregation, up-regulation of gene expression predominated, while after aggregates became visible, down-regulation and up-regulation occurred to the same extent. After aggregates became visible there was a down-regulation of dopamine biosynthesis genes accompanied by down-regulation of dopamine levels in culture, indicating the utility of this model to identify functionally relevant pathways. Furthermore, genes of the anti-oxidant Nrf2-ARE pathway were up-regulated, possibly as a protective mechanism. In parallel, we discovered alterations in genes which may result in increased oxidative stress and damage.</p> <p>Conclusion</p> <p>Up-regulation of gene expression may be more important in HD pathology than previously appreciated. In addition, given the pathogenic impact of oxidative stress and neuroinflammation, the Nrf2-ARE signaling pathway constitutes a new attractive therapeutic target for HD.</p

Machine learning in Huntington’s disease:exploring the Enroll-HD dataset for prognosis and driving capability prediction

Background: In biomedicine, machine learning (ML) has proven beneficial for the prognosis and diagnosis of different diseases, including cancer and neurodegenerative disorders. For rare diseases, however, the requirement for large datasets often prevents this approach. Huntington’s disease (HD) is a rare neurodegenerative disorder caused by a CAG repeat expansion in the coding region of the huntingtin gene. The world’s largest observational study for HD, Enroll-HD, describes over 21,000 participants. As such, Enroll-HD is amenable to ML methods. In this study, we pre-processed and imputed Enroll-HD with ML methods to maximise the inclusion of participants and variables. With this dataset we developed models to improve the prediction of the age at onset (AAO) and compared it to the well-established Langbehn formula. In addition, we used recurrent neural networks (RNNs) to demonstrate the utility of ML methods for longitudinal datasets, assessing driving capabilities by learning from previous participant assessments. Results: Simple pre-processing imputed around 42% of missing values in Enroll-HD. Also, 167 variables were retained as a result of imputing with ML. We found that multiple ML models were able to outperform the Langbehn formula. The best ML model (light gradient boosting machine) improved the prognosis of AAO compared to the Langbehn formula by 9.2%, based on root mean squared error in the test set. In addition, our ML model provides more accurate prognosis for a wider CAG repeat range compared to the Langbehn formula. Driving capability was predicted with an accuracy of 85.2%. The resulting pre-processing workflow and code to train the ML models are available to be used for related HD predictions at: https://github.com/JasperO98/hdml/tree/main . Conclusions: Our pre-processing workflow made it possible to resolve the missing values and include most participants and variables in Enroll-HD. We show the added value of a ML approach, which improved AAO predictions and allowed for the development of an advisory model that can assist clinicians and participants in estimating future driving capability.</p

Generation of 3 spinocerebellar ataxia type 1 (SCA1) patient-derived induced pluripotent stem cell lines LUMCi002-A, B, and C and 2 unaffected sibling control induced pluripotent stem cell lines LUMCi003-A and B

Spinocerebellar ataxia type 1 (SCA1) is a hereditary neurodegenerative disease caused by a CAG repeat expansion in exon 8 of the ATXN1 gene. We generated induced pluripotent stem cells (hiPSCs) from a SCA1 patient and his non-affected sister by using non-integrating Sendai Viruses (SeV). The resulting hiPSCs are SeVfree, express pluripotency markers, display a normal karyotype, retain the mutation (length of the CAG repeat expansion in the ATXN1 gene) and are able to differentiate into the three germ layers in vitro

Amyloid beta accumulations and enhanced neuronal differentiation in cerebral organoids of Dutch-type cerebral amyloid angiopathy patients

IntroductionADutch-type cerebral amyloid angiopathy (D-CAA) is a hereditary brain disorder caused by a point mutation in the amyloid precursor protein (APP) gene. The mutation is located within the amyloid beta (Aβ) domain of APP and leads to Aβ peptide accumulation in and around the cerebral vasculature. There lack of disease models to study the cellular and molecular pathological mechanisms of D-CAA together with the absence of a disease phenotype in vitro in overexpression cell models, as well as the limited availability of D-CAA animal models indicates the need for a D-CAA patient-derived model.MethodsWe generated cerebral organoids from four D-CAA patients and four controls, cultured them up to 110 days and performed immunofluorescent and targeted gene expression analyses at two time points (D52 and D110).ResultsD-CAA cerebral organoids exhibited Aβ accumulations, showed enhanced neuronal and astrocytic gene expression and TGFβ pathway de-regulation.ConclusionsThese results illustrate the potential of cerebral organoids as in vitro disease model of D-CAA that can be used to understand disease mechanisms of D-CAA and can serve as therapeutic intervention platform for various Aβ-related disorders

Bioenergetics in fibroblasts of patients with Huntington disease are associated with age at onset

Objective We aimed to assess whether differences in energy metabolism in fibroblast cell lines derived from patients with Huntington disease were associated with age at onset independent of the cytosine-adenine-guanine (CAG) repeat number in the mutant allele. Methods For this study, we selected 9 pairs of patients with Huntington disease matched for mutant CAG repeat size and sex, but with a difference of at least 10 years in age at onset, using the Leiden Huntington disease database. From skin biopsies, we isolated fibroblasts in which we (1) quantified the ATP concentration before and after a hydrogen-peroxide challenge and (2) measured mitochondrial respiration and glycolysis in real time, using the Seahorse XF Extracellular Flux Analyzer XF24. Results The ATP concentration in fibroblasts was significantly lower in patients with Huntington disease with an earlier age at onset, independent of calendar age and disease duration. Maximal respiration, spare capacity, and respiration dependent on complex II activity, and indices of mitochondrial respiration were significantly lower in patients with Huntington disease with an earlier age at onset, again independent of calendar age and disease duration. Conclusions A less efficient bioenergetics profile was found in fibroblast cells from patients with Huntington disease with an earlier age at onset independent of mutant CAG repeat size. Thus, differences in bioenergetics could explain part of the residual variation in age at onset in Huntington disease

Early molecular layer interneuron hyperactivity triggers Purkinje neuron degeneration in SCA1.

Toxic proteinaceous deposits and alterations in excitability and activity levels characterize vulnerable neuronal populations in neurodegenerative diseases. Using in vivo two-photon imaging in behaving spinocerebellar ataxia type 1 (Sca1) mice, wherein Purkinje neurons (PNs) degenerate, we identify an inhibitory circuit element (molecular layer interneurons [MLINs]) that becomes prematurely hyperexcitable, compromising sensorimotor signals in the cerebellum at early stages. Mutant MLINs express abnormally elevated parvalbumin, harbor high excitatory-to-inhibitory synaptic density, and display more numerous synaptic connections on PNs, indicating an excitation/inhibition imbalance. Chemogenetic inhibition of hyperexcitable MLINs normalizes parvalbumin expression and restores calcium signaling in Sca1 PNs. Chronic inhibition of mutant MLINs delayed PN degeneration, reduced pathology, and ameliorated motor deficits in Sca1 mice. Conserved proteomic signature of Sca1 MLINs, shared with human SCA1 interneurons, involved the higher expression of FRRS1L, implicated in AMPA receptor trafficking. We thus propose that circuit-level deficits upstream of PNs are one of the main disease triggers in SCA1

Underlying molecular mechanisms of DIO2 susceptibility in symptomatic osteoarthritis

Objectives: To investigate how the genetic susceptibility gene DIO2 confers risk to osteoarthritis (OA) onset in humans and to explore whether counteracting the deleterious effect could contribute to novel therapeutic approaches. Methods: Epigenetically regulated expression of DIO2 was explored by assessing methylation of positional CpG-dinucleotides and the respective DIO2 expression in OA-affected and macroscopically preserved articular cartilage from end-stage OA patients. In a human in vitro chondrogenesis model, we measured the effects when thyroid signalling during culturing was either enhanced (excess T3 or lentiviral induced DIO2 overexpression) or decreased (iopanoic acid). Results: OA-related changes in methylation at a specific CpG dinucleotide upstream of DIO2 caused significant upregulation of its expression (ß=4.96; p=0.0016). This effect was enhanced and appeared driven specifically by DIO2 rs225014 risk allele carriers (ß=5.58, p=0.0006). During in vitro chondrogenesis, DIO2 overexpression resulted in a significant reduced capacity of chondrocytes to deposit extracellular matrix (ECM) components, concurrent with significant induction of ECM degrading enzymes (ADAMTS5, MMP13) and markers of mineralisation (ALPL, COL1A1). Given their concurrent and significant upregulation of expression, this process is likely mediated via HIF-2a/RUNX2 signalling. In contrast, we showed that inhibiting deiodinases during in vitro chondrogenesis contributed to prolonged cartilage homeostasis as reflected by significant increased deposition of ECM components and attenuated upregulation of matrix degrading enzymes. Conclusions: Our findings show how genetic variation at DIO2 could confer risk to OA and raised the possibility that counteracting thyroid signalling may be a novel therapeutic approach